Math 147 Section 3.4. Application Example

Similar documents
Math 2331 Linear Algebra

7.6 The Inverse of a Square Matrix

Math 2331 Linear Algebra

Elementary maths for GMT

MATRICES. a m,1 a m,n A =

Chapter 2 Notes, Linear Algebra 5e Lay

Math 4377/6308 Advanced Linear Algebra

MATH 2331 Linear Algebra. Section 2.1 Matrix Operations. Definition: A : m n, B : n p. Example: Compute AB, if possible.

Intermediate Algebra

7.5 Operations with Matrices. Copyright Cengage Learning. All rights reserved.

Row Space, Column Space, and Nullspace

Elementary Matrices. MATH 322, Linear Algebra I. J. Robert Buchanan. Spring Department of Mathematics

Math 240 Calculus III

MATH Topics in Applied Mathematics Lecture 12: Evaluation of determinants. Cross product.

Matrix Algebra. Learning Objectives. Size of Matrix

Lecture 6 & 7. Shuanglin Shao. September 16th and 18th, 2013

Matrix Algebra. Matrix Algebra. Chapter 8 - S&B

Math Matrix Theory - Spring 2012

Math "Matrix Approach to Solving Systems" Bibiana Lopez. November Crafton Hills College. (CHC) 6.3 November / 25

Linear Algebra Practice Problems

Determinants Chapter 3 of Lay

Math 4377/6308 Advanced Linear Algebra

MAC Module 2 Systems of Linear Equations and Matrices II. Learning Objectives. Upon completing this module, you should be able to :

Methods for Solving Linear Systems Part 2

7.1 Solving Systems of Equations

Name: MATH 3195 :: Fall 2011 :: Exam 2. No document, no calculator, 1h00. Explanations and justifications are expected for full credit.

Matrix operations Linear Algebra with Computer Science Application

22m:033 Notes: 3.1 Introduction to Determinants

MATH 1210 Assignment 4 Solutions 16R-T1

Unit 1 Matrices Notes Packet Period: Matrices

Math 4377/6308 Advanced Linear Algebra

Math 3191 Applied Linear Algebra

Matrix Algebra & Elementary Matrices

Chapter 4 Systems of Linear Equations; Matrices

System of Linear Equations

5x 2 = 10. x 1 + 7(2) = 4. x 1 3x 2 = 4. 3x 1 + 9x 2 = 8

For comments, corrections, etc Please contact Ahnaf Abbas: Sharjah Institute of Technology. Matrices Handout #8.

We could express the left side as a sum of vectors and obtain the Vector Form of a Linear System: a 12 a x n. a m2

ENGR-1100 Introduction to Engineering Analysis. Lecture 21. Lecture outline

Matrix Inverses. November 19, 2014

MATH 323 Linear Algebra Lecture 6: Matrix algebra (continued). Determinants.

ENGR-1100 Introduction to Engineering Analysis. Lecture 21

Math 308 Practice Final Exam Page and vector y =

Review for Exam Find all a for which the following linear system has no solutions, one solution, and infinitely many solutions.

Problem 1: Solving a linear equation

Evaluating Determinants by Row Reduction

MAT 1332: CALCULUS FOR LIFE SCIENCES. Contents. 1. Review: Linear Algebra II Vectors and matrices Definition. 1.2.

Components and change of basis

Math 3191 Applied Linear Algebra

Linear Algebra Linear Algebra : Matrix decompositions Monday, February 11th Math 365 Week #4

Math 4377/6308 Advanced Linear Algebra

Linear Algebra I Lecture 8

1 - Systems of Linear Equations

Graduate Mathematical Economics Lecture 1

Undergraduate Mathematical Economics Lecture 1

Math 60. Rumbos Spring Solutions to Assignment #17

ECON 186 Class Notes: Linear Algebra

Linear Equations in Linear Algebra

Linear Equations in Linear Algebra

Math 3C Lecture 20. John Douglas Moore

Section 1.1 System of Linear Equations. Dr. Abdulla Eid. College of Science. MATHS 211: Linear Algebra

Section Gauss Elimination for Systems of Linear Equations

Review Let A, B, and C be matrices of the same size, and let r and s be scalars. Then

MATH Mathematics for Agriculture II

Chapter 1: Systems of Linear Equations and Matrices

CHAPTER 8: Matrices and Determinants

MTH5112 Linear Algebra I MTH5212 Applied Linear Algebra (2017/2018)

MATH 304 Linear Algebra Lecture 20: Review for Test 1.

Solutions to Exam I MATH 304, section 6

MATH 2050 Assignment 8 Fall [10] 1. Find the determinant by reducing to triangular form for the following matrices.

Linear Algebra Math 221

MAC Module 1 Systems of Linear Equations and Matrices I

Solving Systems of Linear Equations Using Matrices

Algebra II Notes Unit Four: Matrices and Determinants

E k E k 1 E 2 E 1 A = B

Recall, we solved the system below in a previous section. Here, we learn another method. x + 4y = 14 5x + 3y = 2

Math 2331 Linear Algebra

a. Define your variables. b. Construct and fill in a table. c. State the Linear Programming Problem. Do Not Solve.

Lecture 3: Gaussian Elimination, continued. Lecture 3: Gaussian Elimination, continued

Relationships Between Planes

Linear Algebra 1 Exam 1 Solutions 6/12/3

Solving Ax = b w/ different b s: LU-Factorization

Topics. Vectors (column matrices): Vector addition and scalar multiplication The matrix of a linear function y Ax The elements of a matrix A : A ij

Math 121. Practice Problems from Chapters 9, 10, 11 Fall 2016

Sections 6.1 and 6.2: Systems of Linear Equations

Section Gauss Elimination for Systems of Linear Equations

2.1 Gaussian Elimination

Lecture 1 Systems of Linear Equations and Matrices

PH1105 Lecture Notes on Linear Algebra.

Lesson 3. Inverse of Matrices by Determinants and Gauss-Jordan Method

Math 313 Chapter 1 Review

MATH 213 Linear Algebra and ODEs Spring 2015 Study Sheet for Midterm Exam. Topics

Solving Linear Systems Using Gaussian Elimination

Section 5.6. LU and LDU Factorizations

3.4 Elementary Matrices and Matrix Inverse

Math Camp Notes: Linear Algebra I

Mathematics 13: Lecture 10

Matrix decompositions

Finite Math - J-term Section Systems of Linear Equations in Two Variables Example 1. Solve the system

Honors Advanced Mathematics Determinants page 1

Transcription:

Math 147 Section 3.4 Inverse of a Square Matrix Matrix Equations Determinants of Matrices 1 Application Example Set up the system of equations and then solve it by using an inverse matrix. One safe investment pays 10% per year, and a more risky investment pays 18% per year. A woman has $149,600 to invest and would like to have an income of $20,000 per year from her investments. How much should she invest at each rate? 2 1

Identity Matrix Recall the identity matrix, I, is a square matrix with 1s down the diagonal and 0s elsewhere. For any square matrix, A, of the same order as I, 3 Inverse Matrix Now we introduce the inverse matrix: Two square matrices A and B are inverses of each other if: Notation: B = A 1 and A = B 1 so (A 1 ) 1 = A 4 2

Inverse Matrix Example: 1 2 1 2 1 0 1 1 1 1 0 1 1 2 1 2 1 0 1 1 1 1 0 1 5 Consider the matrix Inverse Matrix A 1 1 9 1 a matrix A that satisfies A 1 A = I. 1 a b c d a b1 1 c d 9 1. The inverse of A is 1 0 0 1 Multiply out, set it equal to,and equate corresponding entries to come up with a system of 4 equations for the unknowns a, b, c, and d. Then solve that system of unknowns using basic algebra. Use the values you obtain to write down the inverse matrix:a 1. 6 3

Inverse Matrix a b1 1 a9b ab 1 0 c d 9 1 c9d cd 0 1 7 Inverse Matrix We use elementary row operations on augmented matrices to find the inverse of a square matrix: To find the inverse of the square matrix nxn A: 1 Form the augmented matrix [A I], I is the nxn identity matrix 2 Perform elementary row operations until you get an augmented matrix of the form [I B] If A has no inverse, the reduction process will give a row of 0s in the left half of the matrix 3 The matrix B is the inverse of A 8 4

Inverse Matrix 1 2 1 0 1 1 0 1 1r1 + r2 r2 1r2 r2 2r2 + r1 r1 9 4 7 1 0 1 2 0 1 1/4r1 r1 Find the Inverse Matrix 4 7 1 2 7/4r2 + r1 r1 1r1 + r2 r2 4r2 r2 10 5

Matrix Equations Consider the system of equations: 2x + 5y + 4z = 4 x + 4y + 3z = 1 x 3y -2z = 5 Two matrices are equal if they are the same order and each entry in one is equal to its corresponding entry in the other so: 2x5y4z 4 x 4y 3z 1 x3y2z 5 Each is a 3 x 1 matrix and corresponding elements are equal. 11 Matrix Equations Lets factor the left hand matrix: 2x5y4z 4 x 4y 3z 1 x3y2z 5 12 6

Matrix Equations Now let s multiply both sides of this equation by the inverse of the first matrix. 1 2 5 4 1 2 1 1 4 3 5 8 2 1 3 2 7 11 3 1 2 1 2 5 4 x 1 2 1 4 5 8 2 1 4 3 y 5 8 2 1 7 11 3 1 3 2 z 7 11 3 5 13 Matrix Equations 1 0 0 x 3 0 1 0 y 2 0 0 1 z 2 OR Inverse matrices can be used to solve systems of equations if the system has a unique solution. System AX = B has a unique solution if and only if A 1 exists. 14 7

Inverse of 2x2 Matrix a A c b d 1 1 d b A ad bc c a Provided ad bc 0. If ad bc = 0, A 1 does not exist. 15 Determinants of Matrices The determinant of a 2 x 2 matrix is a b a b DET ad bc c d c d notation is like matrix but without the hooks on the lines 16 8

Determinants of Matrices For 3 x 3 matrix a b c d e f g h i 17 Determinants of Matrices If the determinant of a matrix B is zero, then B 1 does not exist, and if B is the coefficient matrix of a system of equations, there is no unique solution to the system. 18 9

Matrix Equations Example: using the calculator. 2x y 2z = 2 3x y + z = 3 x + y z = 7 Coefficient Matrix: Determinant: 2 1 2 3 1 1 1 1 1 19 Matrix Equations (cont.) Example: using the calculator. 2x y 2z = 2 3x y + z = 3 x + y z = 7 20 10

Solve System Using Matrix Equation x + y + 2z = 8 2x + y + z = 7 2x + 2y + z = 10 21 Application Example One safe investment pays 10% per year, and a more risky investment pays 18% per year. A woman has $149,600 to invest and would like to have an income of $20,000 per year from her investments. How much should she invest at each rate? x is $ in safe investment; y is $ in riskier investment. 22 11

Example A product is made by only two competing companies. Suppose Company X retains two-thirds of its customers and loses one-third to Company Y each year, and Company Y retains three-quarters of its customers and loses one-quarter to Company X each year. We can represent the number of customers each company had last year by: x0 y 0 where x 0 is the number Company X had and y 0 is the number Company Y had. 23 Example The number that each will have this year can be represented by 2 1 x 3 4x0 y 1 3 y 0 3 4 If Company X has 1900 customers and Company Y has 1700 customers this year, how many customers did each have last year? 24 12

Example 2 1 1900 3 4x 0 1700 1 3 y 0 3 4 25 13